John Wanamaker, the innovative Philadelphia merchant who pioneered the modern
department store in the Gilded Age, was such a fan of newspapers that he is
credited with buying the first full-page ad.

But even
Wanamaker knew that the most efficient form of advertising available in the
1890s wasn’t terribly efficient at all. “Half the money I spend on advertising
is wasted,” he is famously reported to have said. “The trouble is, I don’t know
which half.”

Nowadays, Wanamaker could find out, with
considerable precision, by hiring Applied Predictive Technologies (APT), a
Virginia-based company that mines all manner of data to determine not only the
optimum ways to buy advertising but also where to locate bank branches and which
under-performing entrees to nix from restaurant menus.

In
fact, as we will see in a moment, a modern-day retailer did hire APT to
scrutinize the efficacy of its ad expenditures. While publishers won’t be
thrilled with the results, the study is a valuable lesson for media companies in
the power of Big Data to either support—or subvert—their businesses. First, the
background:

A privately held company, APT received a hefty
$100 million in equity capital last year from Goldman Sachs, making it one of
the biggest players in the world of predictive analytics, the practice of
sifting mounds of Big Data for patterns that help companies make money, save
money or, ideally, do both at the same time.

With customers
such as Walmart, Lowe’s, Office Depot, PetSmart, CVS, Target, Walgreen’s and
many other global merchants, APT asserts that it captures and crunches 20
percent of data generated in the “U.S. retail economy.” It bounces this rich
transactional data against everything from weather records to Twitter streams to
help companies “measure the profit impact of pricing, marketing, merchandising,
operations and capital initiatives.”

Given the roughly $14
billion that national and local brands spend annually on newspaper advertising
in the United States, it was only a matter of time before one of them asked APT
to answer the question that vexed John Wanamaker: Which advertising dollars are
being wasted?

In a white paper published at its website, APT
reports that it ran the numbers for an unidentified national “big-box” retailer
with a $100 million advertising budget. “On average,” APT stated, “newspaper
advertising did not pay back,” unless the merchant had saturated a market with a
large number of stores. “In markets with low presence, the cost per store far
exceeded the incremental marginal dollars created by the [ad] circular,” said
APT. “Removing underperforming markets eliminated an additional $5 million in
waste from the marketing budget, while having minimal impact on revenue.”

Because that “waste” represents publisher revenues, the
problem for local media companies is obvious. If this sort of analysis catches
on widely—and it’s likely that it will—then it will play havoc with the business
models of local publishers and broadcasters. Armed with better data than ever
about the efficiency of their ads, marketers are bound to either bargain for
lower rates or cut spending. Or, both.

The consolation for
local media companies at the moment is that only the largest merchants have the
sophistication, resources and motivation to employ services like APT. But this
technology—like all technology—will get faster, better, cheaper and become
widely available in the fullness of time. As the awareness and adoption of
predictive analytics inevitably ramps up, local media will be threatened.

Companies like Google, Apple, Facebook, Amazon and dozens of
others are investing heavily in capturing as much data as they can from mobile
devices, digital media consumption, social activities and online purchases. The
current and future advertising, subscription and commerce businesses being
pursued by the tech powerhouses depends on obtaining the maximum amount of
actionable intelligence from as many individuals as possible, including who they
are, how much money they make, where they live, who they know, that they are
reading, where they are going, what they have bought, which videos they have
uploaded, what they are shopping for and—most precious of all—how to generate
more cash by influencing their future behavior.

One way the
big tech companies can capture more data is by offering cheap or free analytical
services to the Main Street businesses that are the core clientele for every
local media company. The businesses get cool, new marketing tools and the
techies get tons of additional data.

Local media companies
can defend against this threat—and build strong businesses for themselves in the
future—by getting ahead of the tech behemoths. In other words, they need to
establish themselves as savvy digital marketing Sherpas before the Big Data guys
get there.

Because we are in the early days of Big Data,
there is time for local media companies to get up to speed. But they have little
time to lose.

Alan D. Mutter is a former newspaper editor and
Silicon Valley CEO who today serves as an adviser to media and technology
companies. He blogs at Reflections of a Newsosaur (www.newsosaur.blogspot.com).